Design of a bilateral filter for noise reduction in contrast-enhanced micro-computed tomography

Abstract

Noise amplification is an important concern in contrast-enhanced (CE) x-ray imaging, in which subtraction techniques are commonly used. In recent years, CE micro-computed tomography (micro-CT) has been used to assess tumor vascularization in animal models of cancer, increasing the necessity to implement noise reduction methods that also allow preserving the detail in the resulting images. This work aimed at designing a bilateral filter (BF) for noise reduction in CE micro-CT for single-energy (SE) and dual-energy (DE) imaging protocols. A classic BF performs smoothing on voxels with similar intensities, while it reduces the contribution of voxels with different intensities, for example, around the edges. In this work, the optimal BF parameters and their performance were evaluated with image quality metrics for the SE and DE protocols: noise (quantified as the standard deviation of the CT number of water), spatial resolution (evaluated with the modulation transfer function), and contrast-to-noise ratio (CNR, evaluated with an iodinated phantom). After the optimal BF parameters were chosen for each imaging protocol, the performance of the designed BF was further evaluated with in vivo SE and DE images of an animal model of breast cancer. Results showed that the designed BF reduced the noise and maintained the spatial resolution in the filtered images compared to the non-filtered images; moreover, the CNR quantified in the images of the iodinated phantom increased both pre- and post- subtraction. The filtered SE and DE images of the animal model of breast cancer showed an adequate level of smoothing, a better definition of tumor boundaries, and the preservation of vascular structures, compared to the non-filtered images. In conclusion, the BF implemented in this work improved the image quality of filtered CE micro-CT images for phantom and in vivo studies, which validates its use in the study of tumor vascularization in animal models of cancer.